Creating Mutual Gains to Leverage a Racially Diverse Workforce: The Effects of Firm-Level Racial Diversity on Financial and Workforce Outcomes Under the Use of Broad-Based Stock Options
Bibliographic record
Abstract
Despite substantial scholarly attention to workforce demographic diversity, existing research is limited in understanding whether or in what contexts firm-level racial diversity relates to performance and workforce outcomes of the firm. Drawing on social interdependence theory along with insights from social exchange and psychological ownership theories, we propose that the use of broad-based stock options granted to at least half the workforce creates the conditions supporting a positive relationship between workforce racial diversity and firm outcomes. We examine this proposition by analyzing panel data from 155 companies that applied for the “100 Best Companies to Work For” competition with responses from 109,314 employees over the five-year period from 2006 to 2010 (354 company-year observations). Findings revealed that racial diversity was positively related to subsequent firm financial performance and individual affective commitment and was not significantly associated with subsequent voluntary turnover rates, when accompanied by a firm’s adoption of broad-based stock options. However, under the nonuse of broad-based stock options, racial diversity was significantly related to higher voluntary turnover rates and lower employee affective commitment, with no financial performance gains. By documenting the beneficial effects of financial incentives in diverse workplaces, this paper extends theory asserting the value of incentives for performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".